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1) pertaining to the topic assigned to your group – identify gaps that need to be bridged in order to improve the science of behavior change – all the way from fundamental science to commercialization – and 2) Develop an outline for the white paper of the sections that would be needed to write this up for a white paper for our funders and (peer reviewed) publications for broader audiences.

Topic: Good enough: What are the new metrics of success? What can we imagine measuring – observables, quantifiables – speed of technological development – how do we match our methodologies of evaluation to the new world of fast technological development and extremely nimble evaluation technologies – we can measure everything all the time.


Members
Members identify gaps that need to be bridged in order to improve the science of behavior change – all the way from fundamental science to commercialization – and 2) Develop an outline for the white paper of the sections that would be needed to write this up for a white paper for our funders and (peer reviewed) publications for broader audiences.

  • Donna Spruijt-Metz

  • Bonnie Spring

  • Daniel E. Rivera

  • NielsBoye

  • Susan Michie

  • Pamela Kato

  • AnaPaiva

  • Scribe: OutiKenttä


What can we imagine measuring observables quantifiables
What can we imagine measuring – observables, identify gaps that need to be bridged in order to improve the science of behavior change – all the way from fundamental science to commercialization – and 2) Develop an outline for the white paper of the sections that would be needed to write this up for a white paper for our funders and (peer reviewed) publications for broader audiences.quantifiables

  • Biological aspects (trait):

    • variation preference/tolerance/ability to self-regulate

    • Satiety

    • Genetics –proclivity, effect on health

    • Metabolic markers: insulin resistance, hunger hormones

  • Present physiological state (state)

  • Past experience (proximal to distal)

  • Past repeated/habitual behavior and how habits ‘bleed’ into new habits (you can model when the behavior becomes a habit – we have a habit modeler)

  • Social& geographical context

  • Cognitive: Drive Plans Beliefs Goals

  • Emotional: Arousal, impulses, inhibition, attraction, repulsion, guilt – SPINOZA

  • Motives: Wants & needs, etc.

  • Metcognition: Morals, identity

  • Skills: Self-regulation


Where do we need to go
Where do we need to go? identify gaps that need to be bridged in order to improve the science of behavior change – all the way from fundamental science to commercialization – and 2) Develop an outline for the white paper of the sections that would be needed to write this up for a white paper for our funders and (peer reviewed) publications for broader audiences.

  • Have a sense of how to relate theoretical models and data from modeling – or falsifying theory (finally)

  • Dinosaurs driving our models are constraining us. What is our relationship to these theories? Are they modifiable?

  • These theories existed to drive behavior change: Lets give them a head to head testing against each other in real-time feedback loops. Undo the sacred status of some theories.

  • Use immediate feedback using ICT, nimble and fast n = 1 feedback loop – get real-time cognitive interviewing in the field at the construct level.

  • Restore the appropriate relationship between theory and data.


Or is this business as usual we need a parallel trail
Or… is this business as usual? identify gaps that need to be bridged in order to improve the science of behavior change – all the way from fundamental science to commercialization – and 2) Develop an outline for the white paper of the sections that would be needed to write this up for a white paper for our funders and (peer reviewed) publications for broader audiences.We need a parallel trail

  • How can we get out of the box?

  • Scrap everything and start over?

  • Can we be more disruptive

  • Concurrent strain of research that is action driven. Participatory design, theory co-produced by users.

  • Start with something/someone/games/commercials/ who is changing behavior and find out what works? What really can change behavior? Look at that, discover working ingredients, Iterate what you learn and maybe even combine with older theories at some point.

  • Culture of preparing for evaluating interventions in advance.

  • Culture of collaboration across fields


Release my inner innovator methodologies
Release my inner innovator: Methodologies identify gaps that need to be bridged in order to improve the science of behavior change – all the way from fundamental science to commercialization – and 2) Develop an outline for the white paper of the sections that would be needed to write this up for a white paper for our funders and (peer reviewed) publications for broader audiences.

  • Methodology of rapid evaluation using collaborative network RCT on one platform where things can be nimble and recruitment can be fast.

  • Also N=1 fast iterative systems science models that can dial up and down various constructs and toss those that are not working at some decision point for a particular ‘type’ of participant

  • Pushing for open source of games, apps, etc. so that we can be learning from the developments in this space. How to resolve tension between IP needs and scientific needs. Need for discussion.


Metrics of success
Metrics of Success? identify gaps that need to be bridged in order to improve the science of behavior change – all the way from fundamental science to commercialization – and 2) Develop an outline for the white paper of the sections that would be needed to write this up for a white paper for our funders and (peer reviewed) publications for broader audiences.

  • Prediction of behavior?

  • Keep up with technology

  • Get under the hood of models and understand the right components

  • Learn methodology of how to build better models.

  • Nimble theories – modular theories that pertain to certain people/behaviors/etc.

  • See how these relate to ‘old’ theories and scrap where data dictates

  • Culture of iteration and open-mindedness and continuous learning.


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